1. Field of the Invention
The present invention relates generally to a method for encoding data, and in particular, to a method for encoding a low-density parity check (LDPC) code.
2. Description of the Related Art
In general, a communication system encodes transmission data before transmission to increase stability of transmission, and prevents excessive retransmissions to increase transmission efficiency. For coding the transmission data, the mobile communication system uses Convolutional Coding, Turbo Coding, and Quasi Complementary Turbo Coding (QCTC). The use of the coding schemes stated above contributes to an increase in stability of data transmission and transmission efficiency.
Recently, wireless communication systems are evolving into advanced wireless communication systems capable of transmitting data at very high speed. The advanced wireless communication system desires to transmit data at higher speed. Accordingly, there is a demand for an advanced coding scheme capable of obtaining higher efficiency than that of the current coding schemes stated above.
Low-density parity check (LDPC) coding is provided as a new coding scheme to meet the demand. A detailed description of the low-density parity check code will now be described herein below. The low-density parity check code was first proposed by Gallager in the early 1960s, and reviewed by MacKay in the late 1990s. The low-density parity check code reviewed by MacKay is based on sum-product algorithm. Since the use of belief propagation decoding, the low-density parity check code has started to attract public attention as a code capable of showing excellent performance approximating the Shannon capacity limit.
Thereafter, Richardson and Chung proposed a density evolution technique for tracing a variation according to iteration in probability distribution of messages generated and updated during decoding on a factor graph constituting a low-density parity check code. For the density evolution technique and infinite iteration on a cycle-free factor graph, Richardson and Chung invented a channel parameter (or threshold) capable of enabling error probability to converge into ‘0’. That is, Richardson and Chung proposed degree distribution capable of maximizing channel parameters of variable nodes and check nodes on the factor graph. In addition, Richardson and Chung theoretically showed that such a case can be applied even to an LDPC code with a finite length in which there are cycles.
In addition, Richardson and Chung showed that theoretical channel capacity of an irregular LDPC code can approximate the Shannon capacity limit up to only 0.0045 dB using the density evolution technique. In particular, Flarion Co., leading realization of design and hardware (H/W) of the LDPC code, has proposed a multi-edge type vector LDPC code capable of realizing a parallel decoder having a frame error rate lower than that of a turbo code even for an LDPC code with a short length.
The LDPC code is treated as a powerful alternative to the turbo code in the next generation mobile communication system. This is because of parallel structure and low complexity of the LDPC code for decoder realization, and low error floor and good frame error rate in terms of performance. Therefore, it is expected that the future researches will provide LDPC codes having better characteristics.
However, in realization, the current LDPC code is more complex than the turbo code in encoding process, and requires a structure of an optimized code capable of providing better performance than the turbo code at a short frame size. Although active researches have been made to solve this problem, there has been proposed no scheme capable of encoding an optimized LDPC code.